def main( epoch_budget, count, gen_type, gen_args, agent_type, agent_args, env_type, env_args, file_prefix ):
"""
@arg epochs: Maximum number of epochs to use
@arg count: Number of options to learn
@arg agent_type: String name of agent
@arg agent_args: Arguments to the agent constructor
@arg env_type: String name of environment
@arg env_args: Arguments to the environment constructor
"""
env = env_type.create( *env_args )
if gen_type == "betweenness":
options = OptionGenerator.learn_options_from_betweenness( epoch_budget, count, env, env_args, agent_type, agent_args )
elif gen_type == "optimal-betweenness":
options = OptionGenerator.optimal_options_from_betweenness( env, count )
elif gen_type == "small-world":
options = OptionGenerator.learn_options_from_small_world( epoch_budget, count, env, env_args, agent_type, agent_args, *gen_args )
elif gen_type == "optimal-small-world":
options = OptionGenerator.optimal_options_from_small_world( env, count, *gen_args )
else:
raise NotImplemented()
# Save options
f = open("%s.options"%( file_prefix ), "w")
pickle.dump( options, f )
f.close()
def create(height, width, scheme="none", count=20, *args):
"""
@spec - Specification (size, endpoints, barriers); either exactly
specified in a file, or with numeric values in a list
@option_scheme - none|manual|optimal|small-world|random|ozgur's betweenness|ozgur's randomness|end
@n_actions - Number of steps that need to taken
comment : optimal(shortest path to destination)??|random|ozgur's betweenness|ozgur's randomness
"""
env = ArbitraryNavigation.create(height, width)
g = env.to_graph()
gr = g.reverse()
# Percentage
if isinstance(count, str):
count = int(count[:-1])
count = count * env.S / 100
# Add options for all the optimal states
O = []
if scheme == "none":
pass
elif scheme == "random-node":
O = OptionGenerator.optimal_options_from_random_nodes(env, count, *args)
elif scheme == "random-path":
O = OptionGenerator.optimal_options_from_random_paths(env, count, *args)
elif scheme == "betweenness":
O = OptionGenerator.optimal_options_from_betweenness(env, count, *args)
elif scheme == "small-world":
O = OptionGenerator.optimal_options_from_small_world(env, count, *args)
elif scheme == "betweenness+small-world":
O = OptionEnvironment.optimal_options_from_betweenness(env, count)
count_ = count - len(O)
O += OptionEnvironment.optimal_options_from_small_world(env, count_, *args)
elif scheme == "load":
O = OptionGenerator.options_from_file(*args)[:count]
else:
raise NotImplemented()
return OptionEnvironment(
ArbitraryNavigationOptions, env.S, env.A, env.P, env.R, env.R_bias, env.start_set, env.end_set, O
)
def create( height, width, scheme = 'none', count = 20, *args ):
"""
@spec - Specification (size, endpoints, barriers); either exactly
specified in a file, or with numeric values in a list
@option_scheme - none|manual|optimal|small-world|random|ozgur's betweenness|ozgur's randomness|end
@n_actions - Number of steps that need to taken
comment : optimal(shortest path to destination)??|random|ozgur's betweenness|ozgur's randomness
"""
env = ArbitraryNavigation.create( height, width )
g = env.to_graph()
gr = g.reverse()
# Percentage
if isinstance(count,str):
count = int(count[:-1])
count = count*env.S/100
# Add options for all the optimal states
O = []
if scheme == "none":
pass
elif scheme == "random-node":
O = OptionGenerator.optimal_options_from_random_nodes( env, count, *args )
elif scheme == "random-path":
O = OptionGenerator.optimal_options_from_random_paths( env, count, *args )
elif scheme == "betweenness":
O = OptionGenerator.optimal_options_from_betweenness( env, count, *args )
elif scheme == "small-world":
O = OptionGenerator.optimal_options_from_small_world( env, count, *args )
elif scheme == "betweenness+small-world":
O = OptionEnvironment.optimal_options_from_betweenness( env, count )
count_ = count - len( O )
O += OptionEnvironment.optimal_options_from_small_world( env, count_, *args )
elif scheme == "load":
O = OptionGenerator.options_from_file( *args )[:count]
else:
raise NotImplemented()
return OptionEnvironment( ArbitraryNavigationOptions, env.S, env.A, env.P, env.R, env.R_bias, env.start_set, env.end_set, O )
comment : optimal(shortest path to destination)??|random|ozgur's betweenness|ozgur's randomness
"""
env = Rooms.create( spec, K )
# Percentage
if isinstance(count,str):
count = int(count[:-1])
count = count*env.S/100
# Add options for all the optimal states
O = []
if scheme == "none":
pass
elif scheme == "random-node":
O = OptionGenerator.optimal_options_from_random_nodes( env, count, *args )
elif scheme == "random-path":
O = OptionGenerator.optimal_options_from_random_paths( env, count, *args )
elif scheme == "betweenness":
O = OptionGenerator.optimal_options_from_betweenness( env, count, *args )
elif scheme == "small-world":
O = OptionGenerator.optimal_options_from_small_world( env, count, *args )
elif scheme == "betweenness+small-world":
O = OptionEnvironment.optimal_options_from_betweenness( env, count )
count_ = count - len( O )
O += OptionEnvironment.optimal_options_from_small_world( env, count_, *args )
elif scheme == "load":
O = OptionGenerator.options_from_file( count, *args )
else:
raise NotImplemented()
comment : optimal(shortest path to destination)??|random|ozgur's betweenness|ozgur's randomness
"""
env = Rooms.create( spec, K )
# Percentage
if isinstance(count,str):
count = int(count[:-1])
count = count*env.S/100
# Add options for all the optimal states
O = []
if scheme == "none":
pass
elif scheme == "random-node":
O = OptionGenerator.optimal_options_from_random_nodes( env, count, *args )
elif scheme == "random-path":
O = OptionGenerator.optimal_options_from_random_paths( env, count, *args )
elif scheme == "betweenness":
O = OptionGenerator.optimal_options_from_betweenness( env, count, *args )
elif scheme == "small-world":
O = OptionGenerator.optimal_options_from_small_world( env, count, *args )
elif scheme == "betweenness+small-world":
O = OptionEnvironment.optimal_options_from_betweenness( env, count )
count_ = count - len( O )
O += OptionEnvironment.optimal_options_from_small_world( env, count_, *args )
elif scheme == "load":
O = OptionGenerator.options_from_file( count, *args )
else:
raise NotImplemented()
